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Ajani, J.

Publications and source records attributed to Ajani, J..

3 recordsLinked to original sources

ARID1A deficiency unleashes centromeric RNA transcription to drive chromosomal instability and boosts PKMYT1 inhibitor efficacy via RNA sensing

Cancer gene-associated mutations and molecular hallmarks of chromosomal instability (CIN) are unexpectedly common in histologically normal cells and tissues. These emerging findings challenge the binary distinction between "normal" and "cancerous" cells and suggest that early tumorigenesis may commence against a background of widespread yet largely tolerated genomic instability. However, it remains largely unexplored how a cancer gene-associated mutation can initiate the development of CIN-like states in non-malignant cells and drive tumor evolution. ARID1A, a chromatin remodeling factor, was identified as the most frequently mutated gene in both gastric normal epithelium and tumors. This distinctive molecular convergence presents an opportunity to elucidate the mechanisms by which a cancer-associated gene facilitates the initiation of early CIN phenotypes and develop effective antitumor strategies. In the present study, using primary human gastric organoids, we employed optical genome mapping (OGM) and live-imaging technologies to demonstrate that ARID1A depletion induced a wide spectrum of structural variants (SVs), copy number variants (CNVs), and chromosomal segregation errors, characteristic features of CIN at a very early stage of gastric tumorigenesis. Mechanistically, ARID1A bound centromere repetitive satellite DNA (satDNA) sequences. Its SWI/SNF-associated chromatin remodeling activity was required for suppressing satDNA transcription and the production of -SatRNA, through restricting RNAPII elongation. Consequently, ARID1A depletion led to overexpression of -SatRNA, and a higher incidence of sister chromatid exchange (SCE), a sensitive indicator of CIN. Importantly, the elevated -SatRNA expression in ARID1A-deficient cells further established a dual therapeutic vulnerability for G2/M checkpoint blockade, such as PKMYT1 inhibitor (PKMYTi), by concurrently aggregating CIN-induced cell death and activating self-dsRNA sensing-mediated innate immune response. Notably, PKMYTi markedly promoted -SatRNA expression, aberrant release of these self-derived dsRNAs into the cytosol and a robust activation of the RIG/MDA5-MAVS-depenent type-I interferon response in ARID1A-depleted cells. As expected, PKMYTi potentiated the efficacy of immunotherapy in ARID1A-deficient gastric tumors. Together, our findings reveal that ARID1A deficiency unleashes centromeric -SatRNA transcription, which sets the molecular stage for tumor evolution and targeted therapy by coordinately inducing CIN and self-dsRNA-induced innate immune responses.

cancer biology↗

Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcome

Intra-tumor heterogeneity is characterized by a diverse population of tumor clones and subclones which are important drivers of tumor evolution and therapeutic response. However, accurate subclonal reconstruction at scale remains challenging. We developed a machine learning tool, CliPP, and surveyed 9,972 tumors from 32 cancer types. We found that high subclonal mutation load (sML), the fraction of subclonal single nucleotide variants (SNVs) to all SNVs in the coding region, was prognostic of survival (progression free survival or overall survival) in 18 cancer types. In 14 cancers with low to moderate tumor mutation burden (TMB), high sML was associated with better prognosis. In immunotherapy trials for 42 metastatic prostate cancer (mCRPC), high sML was predictive of favorable response to ipilimumab and associated with increased CD8+ T-cell infiltration and decreased macrophage population. A validation using 613 whole-genomes of esophageal adenocarcinoma confirms the favorable effect of high sML and the observed tumor-associated macrophage. Our study identifies sML as a key feature of cancer, suggesting a biphasic relationship between evolutionary dynamics and differential immune environments. Finally, sML may serve as an orthogonal approach to identify likely responders of immune checkpoint blockade in low to moderate TMB tumors.

genomics↗

iTALK: an R Package to Characterize and Illustrate Intercellular Communication

Crosstalk between tumor cells and other cells within the tumor microenvironment (TME) plays a crucial role in tumor progression, metastases, and therapy resistance. We present iTALK, a computational approach to characterize and illustrate intercellular communication signals in the multicellular tumor ecosystem using single-cell RNA sequencing data. iTALK can in principle be used to dissect the complexity, diversity, and dynamics of cell-cell communication from a wide range of cellular processes.

cancer biology↗